blakeblackshear.frigate/frigate/embeddings/maintainer.py

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"""Maintain embeddings in Chroma."""
import base64
import io
import logging
import threading
from multiprocessing.synchronize import Event as MpEvent
from typing import Optional
import cv2
import numpy as np
from peewee import DoesNotExist
from PIL import Image
from frigate.comms.events_updater import EventEndSubscriber, EventUpdateSubscriber
from frigate.comms.inter_process import InterProcessRequestor
from frigate.config import FrigateConfig
from frigate.const import UPDATE_EVENT_DESCRIPTION
from frigate.events.types import EventTypeEnum
from frigate.genai import get_genai_client
from frigate.models import Event
from frigate.util.image import SharedMemoryFrameManager, calculate_region
from .embeddings import Embeddings, get_metadata
logger = logging.getLogger(__name__)
class EmbeddingMaintainer(threading.Thread):
"""Handle embedding queue and post event updates."""
def __init__(
self,
config: FrigateConfig,
stop_event: MpEvent,
) -> None:
threading.Thread.__init__(self)
self.name = "embeddings_maintainer"
self.config = config
self.embeddings = Embeddings()
self.event_subscriber = EventUpdateSubscriber()
self.event_end_subscriber = EventEndSubscriber()
self.frame_manager = SharedMemoryFrameManager()
# create communication for updating event descriptions
self.requestor = InterProcessRequestor()
self.stop_event = stop_event
self.tracked_events = {}
self.genai_client = get_genai_client(config.genai)
def run(self) -> None:
"""Maintain a Chroma vector database for semantic search."""
while not self.stop_event.is_set():
self._process_updates()
self._process_finalized()
self.event_subscriber.stop()
self.event_end_subscriber.stop()
self.requestor.stop()
logger.info("Exiting embeddings maintenance...")
def _process_updates(self) -> None:
"""Process event updates"""
update = self.event_subscriber.check_for_update()
if update is None:
return
source_type, _, camera, data = update
if not camera or source_type != EventTypeEnum.tracked_object:
return
camera_config = self.config.cameras[camera]
if data["id"] not in self.tracked_events:
self.tracked_events[data["id"]] = []
# Create our own thumbnail based on the bounding box and the frame time
try:
frame_id = f"{camera}{data['frame_time']}"
yuv_frame = self.frame_manager.get(frame_id, camera_config.frame_shape_yuv)
data["thumbnail"] = self._create_thumbnail(yuv_frame, data["box"])
self.tracked_events[data["id"]].append(data)
self.frame_manager.close(frame_id)
except FileNotFoundError:
pass
def _process_finalized(self) -> None:
"""Process the end of an event."""
while True:
ended = self.event_end_subscriber.check_for_update()
if ended == None:
break
event_id, camera, updated_db = ended
camera_config = self.config.cameras[camera]
if updated_db:
try:
event: Event = Event.get(Event.id == event_id)
except DoesNotExist:
continue
# Skip the event if not an object
if event.data.get("type") != "object":
continue
# Extract valid event metadata
metadata = get_metadata(event)
thumbnail = base64.b64decode(event.thumbnail)
# Embed the thumbnail
self._embed_thumbnail(event_id, thumbnail, metadata)
if (
camera_config.genai.enabled
and self.genai_client is not None
and event.data.get("description") is None
):
# Generate the description. Call happens in a thread since it is network bound.
threading.Thread(
target=self._embed_description,
name=f"_embed_description_{event.id}",
daemon=True,
args=(
event,
[
data["thumbnail"]
for data in self.tracked_events[event_id]
]
if len(self.tracked_events.get(event_id, [])) > 0
else [thumbnail],
metadata,
),
).start()
# Delete tracked events based on the event_id
if event_id in self.tracked_events:
del self.tracked_events[event_id]
def _create_thumbnail(self, yuv_frame, box, height=500) -> Optional[bytes]:
"""Return jpg thumbnail of a region of the frame."""
frame = cv2.cvtColor(yuv_frame, cv2.COLOR_YUV2BGR_I420)
region = calculate_region(
frame.shape, box[0], box[1], box[2], box[3], height, multiplier=1.4
)
frame = frame[region[1] : region[3], region[0] : region[2]]
width = int(height * frame.shape[1] / frame.shape[0])
frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
ret, jpg = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), 100])
if ret:
return jpg.tobytes()
return None
def _embed_thumbnail(self, event_id: str, thumbnail: bytes, metadata: dict) -> None:
"""Embed the thumbnail for an event."""
# Encode the thumbnail
img = np.array(Image.open(io.BytesIO(thumbnail)).convert("RGB"))
self.embeddings.thumbnail.upsert(
images=[img],
metadatas=[metadata],
ids=[event_id],
)
def _embed_description(
self, event: Event, thumbnails: list[bytes], metadata: dict
) -> None:
"""Embed the description for an event."""
description = self.genai_client.generate_description(thumbnails, metadata)
if description is None:
logger.debug("Failed to generate description for %s", event.id)
return
# fire and forget description update
self.requestor.send_data(
UPDATE_EVENT_DESCRIPTION,
{"id": event.id, "description": description},
)
# Encode the description
self.embeddings.description.upsert(
documents=[description],
metadatas=[metadata],
ids=[event.id],
)
logger.debug(
"Generated description for %s (%d images): %s",
event.id,
len(thumbnails),
description,
)